Mathematician and physicist Freeman Dyson has had a career as varied as it has been successful. A former professor of physics at Princeton's Institute for Advanced Study, he has worked on the unification of the three versions of quantum electrodynamics invented by Richard Feynman, nuclear reactors, solid-state physics, ferromagnetism, astrophysics, biology, and the application of useful and elegant math problems. One of his ideas, the Dyson Sphere, was featured in a "Star Trek" episode. Today, Dyson frequently writes about science and technology's relationship to ethics and social issues. Business Insider sat down with him and talked about math, war, the human brain, the education system, and the Orion Project. This interview has been edited for clarity and length. Elena Holodny: Who has most inspired you in either math or science? Dick Feynman ... he has now become famous, to my great joy, because when I knew him he was completely unknown. But I recognized him as being something special. He was only for a short time at Cornell when I was a student and he was a young professor. So I didn't work with him, but I just sat at his feet, literally, and listened to him talk. He was a clown, of course, and also a genius. It was a good combination.

The system is called Recognition and will be running for three months in London up to 27 November 2016, both online and in a small exhibition at the Tate. A nice touch is that it will also take in feedback from matching selections made by viewers themselves at the art museum on Millbank. Created by Fabrica, it's the winner of the IK Prize 2016 for digital innovation, awarded by Tate Britain, in partnership with Microsoft. You can see it in action above, in the match of LS Lowry's Industrial Landscape (from 1955) with a recent construction image of Changi Airport in Singapore… Apparently, Recognition employs multiple artificial intelligence technologies. For example, there is natural language processing to interpret image captions and text, analysing context and subject matter.

Philosophers of science are not known for agreeing with each other--contrariness is part of the job description. But for thousands of years, from Aristotle to Thomas Kuhn, those who study what science is have roughly categorized themselves into two basic camps: "realists" and "anti-realists." In philosophical terms, "anti-realists" or "empiricists" understand science as investigating the properties of observable objects via experiments. Empirical theories are constrained by the experimental results. "Realists," on the other hand, speculate more freely about the possible shape of the unobservable world, often designing mathematical explanations that cannot (yet) be tested. Isaac Newton was a realist, as are string theorists. Most scientists do not lose sleep worrying about philosophical divides. But maybe they should; Albert Einstein certainly did, as did Niels Bohr, and Erwin Schrödinger.

Artificial Lawyer caught up with Cian O'Sullivan, founder of Beagle, the automated contract analysis system that is just celebrating a year and a half of operations and landing VW as a client. We discussed how Beagle came about, why maybe sometimes it's better not to talk to lawyers about AI and how come the company has one of the world's largest auto companies as a client, and then some. Cian O'Sullivan's web camera is not working when Artificial Lawyer calls for a video conference and so is treated to a picture of a soccer pitch in Colombia that the legal tech company founder took on his travels. The international reference makes sense once you start to talk to O'Sullivan. The Canadian travels a lot.

Abstract: With the mission "leave no valuable data behind", we developed techniques for knowledge fusion to guarantee the correctness of the knowledge. This talk starts with describing a few crazy ideas we have tested. The first, known as "Knowledge Vault", used 15 extractors to automatically extract knowledge from 1B Webpages, obtaining 3B distinct (subject, predicate, object) knowledge triples and predicting well-calibrated probabilities for extracted triples. The second, known as "Knowledge-Based Trust", estimated the trustworthiness of 119M webpages and 5.6M websites based on the correctness of their factual information. We then present how we bring the ideas to business in filling the gap between the knowledge at Google Knowledge Graph and the knowledge in the world.

Before Chris White could help disrupt Jihadi finance networks, crush weapons markets, and bust up sex-slave rings with search tools that mine the dark Web, he first had to figure out how to stop himself from plummeting through the open gun door of a banking Black Hawk helicopter. White was on his way to a forward operating base outside Kabul headquarters, as part of a secret intelligence cell to help confront the Taliban and al-Qaida, smash their encrypted online money stream, and win over the hearts and minds of the Afghanistan population. Slight and lanky and 28, White felt Dukakis-ridiculous in his unwieldy body armor and bulbous helmet with "Dr. White" scrawled in marker on duct tape across the front, and with the dust from liftoff, he was finding it hard to breathe. He was still struggling with the unfamiliar seat straps when the pilot hit the stick, sending White sliding toward the hot square of the door and the desert 200 feet below. Down there, Afghanistan was a messy, dangerous place for pretty much everybody. After nearly a decade of U.S.-led war, the American body count had hit 1,000, and civilian casualties were beyond calculation, as President Obama's 30,000-troop surge intensified the fighting that spring. Many feared the situation was only going from bad to worse. The U.S. was escalating drone strikes across the border in Pakistan. And U.S. command was under assault after Gen. Stanley McChrystal, the surge's architect, found himself without a job after he and his staff made disparaging remarks about the commander in chief in some music magazine. It is hard to imagine that only a few weeks earlier, White had been just another impossibly young-looking Harvard postdoc in flip-flops looking forward to a Cambridge summer. Helicopter gunships and war zones weren't on the radar; there were lattes in the square and rock climbing, and on the other side of campus, a prestigious fellowship in the School of Engineering and Applied Sciences, where he was working at the intersection of big data, statistics, and machine learning. He had earned academic pole position and had every expectation it would continue that way forever -- becoming a professor, building a lab, and sniping out white papers from a tenured ivory tower.

This interview is part of a Machine Learning series. We invited Adam Geitgey, Director of Software Engineering at Groupon, to talk about the difference between machine learning and the older artificial intelligence effort and the progress we've made so far. JAXenter: How are you involved in machine learning? Adam Geitgey: My professional background is primarily in traditional software development, not machine learning. I've worked on scaling large-scale websites, building backend systems, building mobile apps and other things like that.

The National Museum of Nature and Science on Tuesday added Lion Corp.'s enzyme-based laundry detergent Top to a list of important historical materials that have had an impact on Japanese lives and culture. Top, which first hit the market in 1979, was among 16 items honored with the designation by the Tokyo museum as "Essential Historical Materials for Science and Technology." With its protein-removing enzymes, the laundry detergent has been popular for its cleaning performance and environmentally friendly formula. Among the other products chosen to make the annual list this year were NEC Corp.'s PC-9801 16-bit personal computer, which debuted in 1982, and the Yagi-Uda antenna, the world's first directional ultrashort-wave antenna that is now used throughout the world in radios and televisions. The antenna, commonly known as the Yagi antenna, derives its name from one of its developers, Dr. Hidetsugu Yagi of Tohoku University.

John McCarthy, an American computer scientist pioneer and inventor, was known as the father of Artificial Intelligence (AI) after playing a seminal role in defining the field devoted to the development of intelligent machines. The cognitive scientist coined the term in his 1955 proposal for the 1956 Dartmouth Conference, the first artificial intelligence conference. The objective was to explore ways to make a machine that could reason like a human, was capable of abstract thought, problem-solving and self-improvement. He believed that "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it." It would prove a challenge that eluded him and which still eludes computer designers today.

A 12-year-old who read The Lord Of The Rings aged five has become the youngest Cornell University freshman in the Ivy School's history. Jeremy Shuler was home-schooled by his parents - both aerospace engineers from Grand Prairie, Texas - and started reading books in English and Korean aged two. To help get him into Cornell, Jeremy's parents moved to Ithaca, where his father, Andy Shuler, took up a post at Lockheed Martin Upstate New York. A 12-year-old who started studying calculus aged 6 has become the youngest Cornell University freshman in the Ivy School's history With his bowl-cut hair, cherubic face and frequent happy laughter, Jeremy is clearly still a child despite his advanced intelligence. He swung in his chair while his parents, who he calls Mommy and Daddy, recounted his early years during an interview at the engineering school where his grandfather is a professor, his father got his doctorate and Jeremy is now an undergrad.